Watching movies to diagnose depression

Michael Breakspear is using cutting edge technology to develop tools that can help people with mental illness (Source: Queensland Institute of Medical Research)

To create the creature Gollum in The Lord of the Rings animators used motion capture technology to map the facial expressions and movements of an actor.

"That's exactly the sort of technology that we should be using in clinical psychiatry," says Professor Michael Breakspear.

Breakspear, a computational biologist and psychiatrist at the Queensland Institute of Medical Research, heads a team researching the potential of facial capture technologies to help people with mental illnesses.

"We film people watching films and work with computer scientists and extract features of their expressions and run it in the same sort of algorithms [used in film]."

By using non-invasive technologies, such as facial recognition, he is hoping to unravel the mysteries of the brain and human behaviour.

Stunning advances

Neuroscience is an area that has changed significantly over the past few years.

"I always think that about 100 years ago we uncovered these amazing mathematical theories about patterns and gravity and all these unifying theories about the physical universe and I think we're at the point now of doing the same sort of thing to biological systems and in particular to the brain," he says.

"The technological advances are stunning and extraordinary. We can image the brain, we can get information in an hour about the brain's structure, function, biochemistry down to the resolution of under a millimetre. We can analyse that data in a way that wasn't possible five to 10 years ago.

"And the way you can take technology from one area and apply them in a different field is amazing," he adds. "We use machine learning and other algorithms that are available in your smart phone and digital camera in our research."

Breakspear's interest in using technology to investigate complex human conditions stems from his background that combines physics, mathematics and psychiatry — degrees he completed simultaneously.

"Every time I went further into the academic realm, I would want to go back and see patients and make a difference in the real world. The more I did that the more that I would want to get back to understanding what was at the heart of things."

As a computational biologist, much of Breakspear's research centres around using imaging technology to unravel the mysteries of how brain cells work together to drive human behaviour.

As a psychiatrist, he hopes to contribute to our understanding of major mental illnesses such as depression and schizophrenia and brain disorders such as autism and dementia.

Facial technology and mental illness

Unlike other health conditions there are no non-subjective tests that can be used by clinicians to diagnose and subtype mental health illness.

"If you go to see a doctor for a surgical problem inevitably the doctor will run a whole lot of tests based on imaging or laboratory tests but in clinical psychiatry there's no laboratory tests, there are no imaging tests."

"The main gap we're trying to address is to use all this amazing modern technology and the mathematics that comes with it to come up with some quantitative measures or tests that real-world clinicians [could use] to help guide their treatment," he says.

And that's where facial recognition technology can help.

Tapping into facial expressions can reveal a lot about a person's mood — or how they interpret other's moods.

"In depression we know that people who are depressed, look depressed.

"We know that people with schizophrenia, particularly if they've had schizophrenia for some time have … almost no emotional expression.

"We believe they also make lots and lots of subtle differences in their eye movement and are not very good at looking at people's eyes or the corners of their mouth," he says.

Breakspear's goal is to develop technology that can be used by clinicians or people with mental health conditions or autism to monitor and adapt their behaviour.

While still a long way to go, the early signs are promising.

"People are happy to sit and watch the films and we have enough data to show that it can be effective, but we're a long way from really building up the scale to the point where we can show how robust it is," he says.

"What we're doing is small scale compared to the film industry, it should be the other way around."